Setup

Load R libraries

library(data.table)
library(ggplot2)
library(ggpubr)
library(tidyr)
library(limma)
library(biomaRt)
library(fgsea)
library(goseq)

theme_set(theme_classic())

cell_type_name = params$cell_type_name
graph_weight = params$graph_weight

cell_type_name
## [1] "cd8"
graph_weight
## [1] "10.0"

Check enrichment of gene sets

Read in gene info and gene set assignments

file_tag = sprintf("%s_BL_%s", cell_type_name, graph_weight)

assayed_genes = scan(sprintf("output/gene_list_%s.txt", file_tag), 
                     what = character(), sep="\n")

gene_sets = scan(sprintf("output/name_s_%s.txt", file_tag), 
                 what = character(), sep="\n")

gene_sets = sapply(gene_sets, strsplit, USE.NAMES=FALSE, split=",")
n_genes   = sapply(gene_sets, length)
names(n_genes) = NULL
summary(n_genes)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##    3.00   23.00   24.00   23.73   25.00   27.00
length(n_genes)
## [1] 40
sort(n_genes)
##  [1]  3 20 21 21 22 22 22 23 23 23 23 24 24 24 24 24 24 24 24 24 24 25 25 25 25
## [26] 25 25 25 25 25 25 25 26 26 26 26 26 27 27 27

Find gene symbols

Find gene symbols from bioMart.

All the gene symbols that can be found in bioMart are consistent with what we have. So no need to run it.

ensembl = useMart("ensembl", dataset = "hsapiens_gene_ensembl")

gene_BM = getBM(attributes = c("hgnc_symbol", "external_gene_name"), 
                filters = "external_gene_name", 
                values = assayed_genes, 
                mart = ensembl)
length(assayed_genes)
dim(gene_BM)
gene_BM[1:2,]

table(assayed_genes %in% gene_BM$external_gene_name)

t1 = table(gene_BM$external_gene_name)
dup = names(t1)[t1 > 1]
gene_BM[gene_BM$external_gene_name %in% dup,]

table(gene_BM$hgnc_symbol == gene_BM$external_gene_name)
w2kp = which(gene_BM$hgnc_symbol != gene_BM$external_gene_name)
gene_BM[w2kp,]

Find gene symbols using the alias2Symbol function from limma.

a2s = rep(NA, length(assayed_genes))
for(i in 1:length(assayed_genes)){
  gi = assayed_genes[i]
  ai = alias2Symbol(gi)
  if(length(ai) > 1){
    print(gi)
    print(ai)
  }
  a2s[i] = ai[1]
}
## [1] "QARS"
## [1] "EPRS1" "QARS1"
## [1] "SEPT2"
## [1] "SEPTIN6" "SEPTIN2"
table(is.na(a2s))
## 
## FALSE  TRUE 
##  1607    42
table(a2s == assayed_genes, useNA = 'ifany')
## 
## FALSE  TRUE  <NA> 
##    42  1565    42
gene_info = data.table(sym_in_data = assayed_genes, sym_limma = a2s)

gene_info[sym_in_data != sym_limma,]
##     sym_in_data sym_limma
##  1:    C10orf91 LINC02870
##  2:    C12orf10      MYG1
##  3:    C12orf45  NOPCHAP1
##  4:     C6orf48    SNHG32
##  5:     C6orf99 LINC02901
##  6:    CXorf40A     EOLA1
##  7:     CXorf57      RADX
##  8:     FAM102A     EEIG1
##  9:     FAM173A    ANTKMT
## 10:     FAM213B    PRXL2B
## 11:       H2AFX      H2AX
## 12:   HIST1H2AG    H2AC11
## 13:   HIST1H2BK    H2BC12
## 14:   HIST1H2BN    H2BC15
## 15:    HIST1H3A      H3C1
## 16:    HIST1H3H     H3C10
## 17:    HIST1H4C      H4C3
## 18:   HIST2H2BF    H2BC18
## 19:    KIAA0391     PRORP
## 20:        QARS     EPRS1
## 21:       SEPT6   SEPTIN6
## 22:       ARNTL     BMAL1
## 23:    C12orf65     MTRFR
## 24:    C16orf72   HAPSTR1
## 25:      CCDC84   CENATAC
## 26:      DOPEY2     DOP1B
## 27:     FAM126B     HYCC2
## 28:    FAM160B1    FHIP2A
## 29:        H1FX     H1-10
## 30:       H2AFJ      H2AJ
## 31:       HEXDC      HEXD
## 32:    HIST1H1C      H1-2
## 33:    HIST1H1D      H1-3
## 34:    HIST1H1E      H1-4
## 35:    KIAA1109     BLTP1
## 36:    KIAA1551     RESF1
## 37:        MKL1     MRTFA
## 38:       NARFL     CIAO3
## 39:       SEPT2   SEPTIN6
## 40:      TARSL2     TARS3
## 41:      TMEM8A     PGAP6
## 42:       WDR60   DYNC2I1
##     sym_in_data sym_limma
gene_info[, gene_symbol := sym_in_data]
gene_info[which(sym_in_data != sym_limma), gene_symbol := sym_limma]

dim(gene_info)
## [1] 1649    3
gene_info[1:5,]
##    sym_in_data sym_limma gene_symbol
## 1:      ABLIM1    ABLIM1      ABLIM1
## 2:  AC004687.1      <NA>  AC004687.1
## 3:  AC004854.2      <NA>  AC004854.2
## 4:  AC007384.1      <NA>  AC007384.1
## 5:  AC007952.4      <NA>  AC007952.4
t1 = table(gene_info$gene_symbol)
table(t1)
## t1
##    1    2 
## 1647    1
gene_info[gene_symbol %in% names(t1)[t1 == 2],]
##    sym_in_data sym_limma gene_symbol
## 1:       SEPT6   SEPTIN6     SEPTIN6
## 2:       SEPT2   SEPTIN6     SEPTIN6
gene_info[sym_in_data == "HIST1H2BC", gene_symbol:="H2BC4"]
gene_info[sym_in_data == "SEPT6", gene_symbol:="SEPTIN6"]
gene_info[sym_in_data == "SEPT2", gene_symbol:="SEPTIN2"]

Prepare gene set information

Gene set annotations (by gene symbols) were downloaded from MSigDB website.

gmtfile = list()
gmtfile[["reactome"]] = "../Annotation/c2.cp.reactome.v2023.2.Hs.symbols.gmt"
gmtfile[["go_bp"]]    = "../Annotation/c5.go.bp.v2023.2.Hs.symbols.gmt"
gmtfile[["immune"]]   = "../Annotation/c7.all.v2023.2.Hs.symbols.gmt"

pathways = list()
for(k1 in names(gmtfile)){
  pathways[[k1]] = gmtPathways(gmtfile[[k1]])
}

names(pathways)
## [1] "reactome" "go_bp"    "immune"
sapply(pathways, length)
## reactome    go_bp   immune 
##     1692     7647     5219

Filter gene sets for size between 10 and 500.

lapply(pathways, function(v){
  quantile(sapply(v, length), probs = seq(0, 1, 0.1), na.rm = TRUE)
})
## $reactome
##     0%    10%    20%    30%    40%    50%    60%    70%    80%    90%   100% 
##    5.0    7.0    9.0   12.0   17.0   23.0   31.0   44.0   71.8  120.9 1463.0 
## 
## $go_bp
##     0%    10%    20%    30%    40%    50%    60%    70%    80%    90%   100% 
##    5.0    6.0    8.0   10.0   14.0   19.0   29.0   46.0   80.8  183.0 1966.0 
## 
## $immune
##   0%  10%  20%  30%  40%  50%  60%  70%  80%  90% 100% 
##    5  162  193  197  199  199  200  200  200  200 1992
for(k1 in names(pathways)){
  p1 = pathways[[k1]]
  pathways[[k1]] = p1[sapply(p1, length) %in% 10:500]
}

Conduct enrichment analysis

dim(gene_info)
## [1] 1649    3
max_n2kp = 10

goseq_res = NULL

for(k in 1:length(gene_sets)){
  if(length(gene_sets[[k]]) < 10) { next }
  
  print(k)
  set_k = paste0("set_", k)
  print(gene_sets[[k]])
  
  genes = gene_info$sym_in_data %in% gene_sets[[k]]
  names(genes) = gene_info$gene_symbol
  table(genes)
  
  pwf = nullp(genes, "hg38", "geneSymbol")

  for(k1 in names(pathways)){
    p1 = pathways[[k1]]
    res1 = goseq(pwf, "hg38", "geneSymbol", 
                 gene2cat=goseq:::reversemapping(p1))
    res1$FDR  = p.adjust(res1$over_represented_pvalue, method="BH")
    
    nD = sum(res1$FDR < 0.1)
    
    if(nD > 0){
      res1 = res1[order(res1$FDR),][1:min(nD, max_n2kp),]
      res1$category = gsub("REACTOME_|GOBP_", "", res1$category)
      res1$category = gsub("_", " ", res1$category)
      res1$category = tolower(res1$category)
      res1$category = substr(res1$category, start=1, stop=81)
      goseq_res[[set_k]][[k1]] = res1
    }
  }
}
## [1] 1
##  [1] "AC008555.5" "AC012645.3" "AC044849.1" "AC087623.3" "AC119396.1"
##  [6] "AC245297.3" "ARRDC2"     "CCL4L2"     "CLDND1"     "CRLF3"     
## [11] "EOMES"      "HIKESHI"    "INTS6L"     "LINC00649"  "PITPNC1"   
## [16] "TRAV8-3"    "TRGV7"      "TRGV8"      "ADGRG1"     "ARHGAP30"  
## [21] "CYTOR"      "FCRL6"      "NECAP1"     "TTC38"      "XCL2"

## [1] 2
##  [1] "AK5"        "CHRM3-AS2"  "COQ8A"      "IGLV1-44"   "LINC00402" 
##  [6] "LST1"       "MATR3-1"    "PDCD4-AS1"  "RETREG1"    "TC2N"      
## [11] "TRAV14DV4"  "TRAV8-2"    "TRBV28"     "TRBV9"      "CLEC16A"   
## [16] "DOCK10"     "HIPK1"      "HRH2"       "IFI27"      "NUTM2B-AS1"
## [21] "PIK3CD"     "POLR2J3-1"  "PPP4R3B"    "PUM3"       "S100A12"   
## [26] "TUT4"

## [1] 3
##  [1] "NUAK2"    "TBCCD1"   "ABCA7"    "ARHGAP10" "BTBD9"    "DMTF1"   
##  [7] "ERBIN"    "FAM126B"  "FAM78A"   "GK5"      "HECA"     "IRF9"    
## [13] "MCTP2"    "MYBL1"    "MYO1F"    "NFATC3"   "NRDC"     "OGA"     
## [19] "PARP15"   "PATL2"    "PIK3R5"   "RASGRP1"  "RNF125"   "SIDT1"   
## [25] "TUT7"     "XIST"

## [1] 4
##  [1] "CCR7"       "FXYD7"      "LTB"        "SLC2A3"     "AC016831.7"
##  [6] "ARHGAP45"   "ARHGEF9"    "ATAD2B"     "BMT2"       "ETFDH"     
## [11] "FAM133B"    "GABPB2"     "GPHN"       "HPS4"       "KAT6B"     
## [16] "LINC02446"  "MARF1"      "OXNAD1"     "PCED1B"     "PNPLA8"    
## [21] "PSMA3-AS1"  "RIPOR2"     "SEC14L1"    "THAP5"      "TMEM131L"  
## [26] "ZNF83"

## [1] 6
##  [1] "HLA-DMB"  "KLRB1"    "KLRC3"    "KLRK1"    "MAN2B1"   "OXA1L"   
##  [7] "TFB2M"    "TIGIT"    "CMKLR1"   "CSNK1G2"  "GALNT10"  "GDPD5"   
## [13] "ITGAM"    "KIR2DL3"  "RAPGEF1"  "SLC20A1"  "SLC38A10" "TIMP1"   
## [19] "TMEM127"  "TMEM181"  "TMEM8A"   "TTC17"

## [1] 7
##  [1] "CCNB1IP1" "ADGRE5"   "ARL4C"    "CARD11"   "CARD16"   "CD52"    
##  [7] "CTSW"     "CX3CR1"   "DDX60L"   "IFITM2"   "ITM2A"    "KDM3B"   
## [13] "KIAA1551" "LAG3"     "LY6E"     "MT2A"     "MYO1G"    "RALGAPB" 
## [19] "S100A11"  "TRAC"     "TRAV12-3" "TRAV17"   "TRAV9-2"  "TRBV11-2"
## [25] "TRGC2"    "ZNF683"

## [1] 8
##  [1] "AIF1"    "CHMP1B"  "NSUN6"   "CASP10"  "CAST"    "CCDC88C" "CD46"   
##  [8] "CELF2"   "CFLAR"   "DDHD1"   "DENND6A" "ITK"     "KCNAB2"  "KDM5A"  
## [15] "KLF3"    "LRBA"    "MTMR6"   "NCKAP1L" "PCYT1A"  "PRKCH"   "RASA3"  
## [22] "RIC3"    "SPG11"   "WDR7"

## [1] 9
##  [1] "ID2"     "ISCA1"   "MAP3K2"  "MSC"     "NDE1"    "SPECC1"  "ABHD17A"
##  [8] "BHLHE40" "DOCK11"  "EFHD2"   "FRYL"    "GSE1"    "LENG8"   "MACF1"  
## [15] "MAP3K3"  "PHF3"    "PLEKHG3" "POLH"    "PRR5L"   "PTPN23"  "SSH1"   
## [22] "STK38"   "WAC"     "ZFYVE16"

## [1] 10
##  [1] "CD27"         "CPNE1"        "CREBL2"       "CYB561A3"     "EPB41L4A-AS1"
##  [6] "FCER1G"       "IER3"         "ITGAE"        "KIR3DL2"      "LRRC23"      
## [11] "NCR1"         "NR4A3"        "NT5DC1"       "SDR42E2"      "SLC38A1"     
## [16] "TMEM107"      "TMEM204"      "TMEM42"       "TSPYL4"       "UIMC1"       
## [21] "ZFAND1"       "PARP4"        "TEP1"         "TRIM38"

## [1] 11
##  [1] "GLA"     "MAT2B"   "ARHGEF3" "ARID5B"  "BROX"    "CAPNS1"  "GCN1"   
##  [8] "GPRIN3"  "IL2RG"   "INO80D"  "KLF2"    "KLF6"    "NCOA7"   "NLRC5"  
## [15] "PLA2G6"  "PLAC8"   "SENP7"   "SLFN12L" "STK17B"  "TOB1"    "USP16"  
## [22] "XAF1"    "ZBP1"    "ZBTB20"  "ZDHHC20"

## [1] 12
##  [1] "THAP9-AS1"   "AKNA"        "AP005482.1"  "CEMIP2"      "DIAPH2"     
##  [6] "GPR174"      "LINC02384"   "MIAT"        "MX2"         "NBEAL2"     
## [11] "OAS2"        "ODF3B"       "PCSK7"       "SAMD9L"      "TBC1D14"    
## [16] "THUMPD3-AS1" "TRANK1"      "TRAPPC11"    "TRAPPC8"     "TRAV19"     
## [21] "TRAV27"      "TRAV4"       "TRBV2"       "TRDV1"       "TRGV10"     
## [26] "TRGV4"       "TSPAN32"

## [1] 13
##  [1] "AC083798.2" "AL121944.1" "ARMH1"      "ATP2B1-AS1" "BBS9"      
##  [6] "FAM213B"    "IGKV3-20"   "INPP4B"     "LRRN3"      "NPIPB4"    
## [11] "NUP58"      "PRAG1"      "RAB33B"     "SLC27A5"    "TNFRSF25"  
## [16] "TRABD2A"    "TRAV12-2"   "TRAV5"      "TRAV8-4"    "TRBV3-1"   
## [21] "TRBV6-1"    "TRBV6-2"    "ZNF749"     "ZNF862"     "MTERF2"    
## [26] "RUFY2"      "SLCO3A1"

## [1] 14
##  [1] "AC007384.1" "AC020911.2" "AC025171.3" "AC083880.1" "AC091271.1"
##  [6] "AC103591.3" "AF213884.3" "AL139246.5" "AL357060.1" "AL451085.1"
## [11] "AL627171.1" "ASL"        "C6orf99"    "HELQ"       "HIPK1-AS1" 
## [16] "IFRD1"      "KCNQ1OT1"   "LINC01465"  "MZF1-AS1"   "NT5C3B"    
## [21] "OSER1-DT"   "PGGHG"      "RGS1"       "TRAV3"      "TRBV7-9"   
## [26] "C16orf72"   "HIVEP3"

## [1] 15
##  [1] "ACTR1B"   "C12orf10" "EIF1"     "EIF2S3"   "EIF3E"    "EIF3G"   
##  [7] "EIF3K"    "EIF3L"    "EIF4A2"   "PAIP2"    "PHLDA1"   "RACK1"   
## [13] "ATAD2"    "DDX60"    "EIF3A"    "EIF4G1"   "EIF4G3"   "LRRFIP1" 
## [19] "MSI2"     "PRRC2C"   "SECISBP2"

## [1] 16
##  [1] "AC004687.1" "AC087239.1" "AL118516.1" "AL138963.3" "ANXA2R"    
##  [6] "ATP5F1A"    "BTG2"       "CCNI"       "CMC1"       "FCMR"      
## [11] "GCSAM"      "GTF3A"      "ICAM3"      "KLRF1"      "MFNG"      
## [16] "NBPF14"     "NOP53"      "PPP1R15B"   "PRR7"       "RTRAF"     
## [21] "SNHG15"     "SNHG9"      "TRG-AS1"    "WDR86"      "WSB1"      
## [26] "ZNF276"

## [1] 17
##  [1] "ARL4A"   "IL6R"    "RGCC"    "TXK"     "UBL7"    "ZC3H12A" "ZNF10"  
##  [8] "CLUH"    "COX19"   "ELMO1"   "ETV6"    "GON4L"   "LONP2"   "NAA25"  
## [15] "NFKBIZ"  "PARP14"  "PARP9"   "PDE4B"   "PHF14"   "PIGF"    "SETD2"  
## [22] "USP34"   "WDR37"   "ZNF557"

## [1] 18
##  [1] "AKTIP"     "GLS"       "HIST1H2BK" "HIST1H2BN" "IL16"      "NCF1"     
##  [7] "PPA1"      "SSR2"      "TBC1D17"   "BDP1"      "CPT1A"     "CYBA"     
## [13] "DHX29"     "FGR"       "NEMF"      "NNT"       "PKD1"      "PPP1R12C" 
## [19] "PTMS"      "UPF2"

## [1] 19
##  [1] "ASAH1"    "ATP5MG"   "CD7"      "GATA3"    "GRAMD1A"  "MZT2A"   
##  [7] "MZT2B"    "PNRC1"    "PPP1R15A" "PTGER4"   "VAMP7"    "CD99"    
## [13] "DNAJB14"  "KLHDC4"   "NUP210"   "PTPN4"    "PTPN7"    "RORA"    
## [19] "ST6GAL1"  "TBX21"    "TUBGCP6"  "ZFAND3"

## [1] 20
##  [1] "ARHGAP9"  "C12orf45" "CXXC5"    "EI24"     "GIMAP1"   "GPR183"  
##  [7] "GSTM1"    "GSTM4"    "LCP2"     "LETMD1"   "PCMTD2"   "PDE7A"   
## [13] "RTN3"     "SESN2"    "TRAT1"    "ARAP2"    "FAM169A"  "LRRC8A"  
## [19] "MCOLN2"   "MICAL2"   "SZT2"     "VPS13A"   "VPS13D"

## [1] 21
##  [1] "CAMK4"    "CMTM7"    "EPHX2"    "EPS8"     "FAM102A"  "HIBADH"  
##  [7] "LDLRAP1"  "NOSIP"    "RCAN3"    "SELL"     "STMN3"    "TCEA3"   
## [13] "TCF7"     "TESPA1"   "TRAV21"   "ZNF575"   "GPANK1"   "HERC3"   
## [19] "HERC6"    "ITPR2"    "MAPK8IP3" "SCRN3"    "SOS1"     "VCAN"    
## [25] "ZNF493"

## [1] 22
##  [1] "AMD1"     "C12orf57" "CD84"     "DTHD1"    "FAM118A"  "GLTP"    
##  [7] "GZMK"     "KLRG1"    "NOCT"     "PIK3IP1"  "RCSD1"    "RGL4"    
## [13] "RSRP1"    "SH2D1A"   "SLC38A2"  "STK17A"   "TOX"      "TRBC1"   
## [19] "TRGV5"    "WARS2"    "CCDC112"  "ERAP2"    "SLK"      "VPS13B"  
## [25] "YPEL1"

## [1] 23
##  [1] "ALOX5AP" "APMAP"   "HDHD3"   "LAPTM5"  "LBH"     "LIME1"   "MATK"   
##  [8] "PTPRCAP" "PTRHD1"  "RHOC"    "THEM4"   "TMEM134" "CBX7"    "CST7"   
## [15] "FGFBP2"  "GZMA"    "GZMB"    "NKG7"    "PHC3"    "PLEK"    "SPON2"  
## [22] "SRGN"    "UBE4A"   "UCP2"

## [1] 24
##  [1] "NT5E"    "SNRPN"   "ZEB1"    "AFF1"    "AFF4"    "ARID1A"  "ARID1B" 
##  [8] "BAZ2A"   "CHD1"    "CRNKL1"  "DGKD"    "NKTR"    "PIP4K2B" "PNN"    
## [15] "PPIG"    "RNF157"  "RNMT"    "RNPC3"   "SCAF8"   "SMG1"    "USP42"  
## [22] "WDR60"

## [1] 25
##  [1] "BTG1"     "FOXP1"    "KLHDC2"   "PPP1R10"  "PRPF38B"  "SAT1"    
##  [7] "SATB1"    "ZBTB10"   "ARHGAP4"  "ASH1L"    "FAM160B1" "HERC1"   
## [13] "MALAT1"   "MORC3"    "NEAT1"    "RUNX3"    "SLTM"     "TCF25"   
## [19] "TFDP2"    "TTF2"     "ZC3H7B"   "ZEB2"     "ZNF335"

## [1] 26
##  [1] "AC004854.2"  "AC015982.1"  "AC016405.3"  "AC027644.3"  "AOAH"       
##  [6] "ARF4-AS1"    "BX284668.6"  "CRTAM"       "CSKMT"       "CXorf40A"   
## [11] "IER5"        "ILF3-DT"     "KLF10"       "KMT2E-AS1"   "MAPRE2"     
## [16] "MTRNR2L8"    "PAPSS1"      "SLC4A4"      "TRAV38-2DV8" "TRBV6-5"    
## [21] "TRBV7-2"     "TRGV9"       "Z93241.1"    "GALNT3"      "RLF"

## [1] 27
##  [1] "HMGCS1"   "RELT"     "TPRKB"    "CAPN15"   "DNAJC13"  "EPSTI1"  
##  [7] "GPATCH2L" "HSH2D"    "IFI44"    "IFI44L"   "IGHA1"    "IGKC"    
## [13] "MBD5"     "MX1"      "PHF11"    "PPM1K"    "PRKX"     "PTPRJ"   
## [19] "RNF213"   "S100A8"   "SPOCK2"   "STK10"    "TTC14"

## [1] 28
##  [1] "LPXN"    "C2CD3"   "CEP164"  "CEP350"  "CTDSPL2" "DENND4C" "ENTPD4" 
##  [8] "GIGYF1"  "HELZ2"   "HIPK3"   "IFIT2"   "IFIT3"   "KIF13B"  "LIMD1"  
## [15] "MAN2C1"  "N4BP1"   "PHACTR4" "PSTPIP2" "REXO1"   "RIF1"    "SMCHD1" 
## [22] "ZCCHC2"  "ZNF292"  "ZNF800"

## [1] 29
##  [1] "CST3"     "CYB5D2"   "GALNT11"  "INTS8"    "PDE3B"    "SAE1"    
##  [7] "ADAM10"   "AHCTF1"   "ASCL2"    "CHST12"   "CTSC"     "DOPEY2"  
## [13] "FAR1"     "GALNT2"   "HLA-DQA1" "HLA-DRB1" "KLRD1"    "LILRB1"  
## [19] "LPCAT1"   "MPPE1"    "MYO9B"    "PDE12"    "PNPLA6"   "PRF1"

## [1] 30
##  [1] "ABCC10"     "AC092683.1" "AC116407.2" "ADCY7"      "AP3M2"     
##  [6] "CCDC84"     "CREBZF"     "ELMOD3"     "GPR132"     "GRK2"      
## [11] "IGKV3-15"   "LINC02256"  "MIGA1"      "PCNX1"      "RUBCN"     
## [16] "SLF2"       "SPATA13"    "TENT5C"     "TRBV4-2"    "TRBV7-6"   
## [21] "TTTY15"     "UTY"        "Z93930.2"   "ZNF652"     "ZNF808"

## [1] 31
##  [1] "COMMD6"   "COTL1"    "RPL41"    "TOMM7"    "TPGS2"    "TRAF3IP2"
##  [7] "YPEL3"    "ARHGAP35" "B2M"      "CD8A"     "CD8B"     "FNDC3B"  
## [13] "GCA"      "HEXDC"    "KIAA0232" "LSS"      "MKL1"     "OAS3"    
## [19] "POLG"     "PRSS23"   "SBK1"     "TAF1D"    "TMSB10"   "TMSB4X"

## [1] 32
##  [1] "CD28"     "TLE4"     "ARAP1"    "C5orf24"  "CCL4"     "CES1"    
##  [7] "CROCC"    "ETNK1"    "GNLY"     "GNPTAB"   "GPR141"   "INPP5D"  
## [13] "KIAA2026" "MKLN1"    "NARFL"    "PDZD4"    "PEX1"     "PEX26"   
## [19] "SEMA4D"   "ST8SIA4"  "SUSD1"    "SYNE1"    "UBR2"     "WDTC1"   
## [25] "YPEL5"

## [1] 33
##  [1] "FCRL3"    "ITGB1BP1" "ANKRD12"  "APOL6"    "BTN3A1"   "CCNH"    
##  [7] "CD38"     "EML4"     "ERICH1"   "FAM13B"   "ITGAL"    "PREX1"   
## [13] "PYROXD1"  "RHOH"     "SLA2"     "SLC35F5"  "SLFN5"    "STAT4"   
## [19] "SYNRG"    "TAOK1"    "TAOK3"    "TIPARP"   "TRBC2"    "UNC13D"  
## [25] "ZAP70"

## [1] 34
##  [1] "AC025164.1" "AL135791.1" "ALKBH7"     "BEX4"       "BNIP3L"    
##  [6] "C6orf48"    "CD40LG"     "COA1"       "HIST1H3H"   "JAML"      
## [11] "LINC02273"  "MCUB"       "MYLIP"      "NR1D1"      "SESN1"     
## [16] "SNHG12"     "TMIGD2"     "TRAV1-2"    "TRAV13-1"   "TRBV20-1"  
## [21] "CISH"       "CRYBG1"     "R3HCC1L"    "RFWD3"      "SETX"

## [1] 35
##  [1] "AC007952.4" "AC245014.3" "CITED2"     "COQ7"       "CSRNP1"    
##  [6] "DYRK4"      "EFCAB2"     "FAM173A"    "GADD45B"    "GLRX5"     
## [11] "IER2"       "KCTD7"      "MPST"       "MZF1"       "NELL2"     
## [16] "NR4A2"      "TCP11L2"    "TGIF1"      "ZFAS1"      "ZFP36L1"   
## [21] "LTBP4"      "PRR14L"     "SETD5"      "ZBTB40"

## [1] 36
##  [1] "C10orf91"    "AC020659.1"  "ANKRD36B"    "ANKRD36C"    "BICRAL"     
##  [6] "CHD9"        "COL6A2"      "COL6A3"      "CPPED1"      "DENND4B"    
## [11] "EHBP1L1"     "IQCG"        "LAIR2"       "MINDY2"      "NLRC3"      
## [16] "RAB27B"      "RNF19A"      "SLC16A1-AS1" "SYTL3"       "TRDC"       
## [21] "TTC16"       "VPS13C"      "VTI1A"       "XCL1"        "ZNF708"

## [1] 37
##  [1] "BACH2"    "EGR1"     "FOSB"     "HIST1H4C" "JUNB"     "MAF1"    
##  [7] "NUCB2"    "RGS10"    "RPL22L1"  "SEPT6"    "SNHG8"    "TSR3"    
## [13] "ACAP3"    "ARRDC3"   "CYTH1"    "FOSL2"    "JUND"     "L3HYPDH" 
## [19] "MAF"      "MIDN"     "POLR3D"

## [1] 38
##  [1] "CD83"     "COG5"     "HMBOX1"   "IKZF2"    "KIF9"     "NXT2"    
##  [7] "ANKRD36"  "ANKRD49"  "BCL9L"    "CD226"    "COG7"     "FNBP1"   
## [13] "INPP4A"   "IRAK4"    "PPP1R16B" "RAP1GAP2" "SPN"      "SSBP3"   
## [19] "THADA"    "UVRAG"    "VPS18"    "VPS39"    "XPO6"

## [1] 39
##  [1] "AL136454.1" "SERINC5"    "ABCA5"      "ADHFE1"     "CHD6"      
##  [6] "DDIT4"      "DDX3Y"      "DUS1L"      "EIF1AY"     "ENOSF1"    
## [11] "FGL2"       "GBP5"       "HECTD4"     "ISG20"      "KDM5D"     
## [16] "KIAA1109"   "LPIN1"      "OSM"        "PARP11"     "RPS4Y1"    
## [21] "SBNO2"      "SUSD6"      "TARSL2"     "ZMIZ2"      "ZNF236"

## [1] 40
##  [1] "CXorf57" "ID1"     "PLK2"    "SBF2"    "ABR"     "ANKRD44" "EHD4"   
##  [8] "EIF4E3"  "FAM53B"  "H6PD"    "MYOM2"   "NEK9"    "NRDE2"   "PPIL2"  
## [15] "PRDM2"   "PTGDS"   "RBSN"    "RREB1"   "SBF1"    "TBC1D2B" "TMX3"   
## [22] "UQCC2"   "ZNF407"  "ZNF827"

for(n1 in names(goseq_res)){
  k = as.numeric(gsub("set_", "", n1))
  print(n1)
  print(gene_sets[[k]])
  print(goseq_res[[n1]])

}
## [1] "set_1"
##  [1] "AC008555.5" "AC012645.3" "AC044849.1" "AC087623.3" "AC119396.1"
##  [6] "AC245297.3" "ARRDC2"     "CCL4L2"     "CLDND1"     "CRLF3"     
## [11] "EOMES"      "HIKESHI"    "INTS6L"     "LINC00649"  "PITPNC1"   
## [16] "TRAV8-3"    "TRGV7"      "TRGV8"      "ADGRG1"     "ARHGAP30"  
## [21] "CYTOR"      "FCRL6"      "NECAP1"     "TTC38"      "XCL2"      
## $go_bp
##                           category over_represented_pvalue
## 943      forebrain regionalization             2.99102e-05
## 4491 telencephalon regionalization             2.99102e-05
##      under_represented_pvalue numDEInCat numInCat        FDR
## 943                         1          2        2 0.07015437
## 4491                        1          2        2 0.07015437
## 
## [1] "set_15"
##  [1] "ACTR1B"   "C12orf10" "EIF1"     "EIF2S3"   "EIF3E"    "EIF3G"   
##  [7] "EIF3K"    "EIF3L"    "EIF4A2"   "PAIP2"    "PHLDA1"   "RACK1"   
## [13] "ATAD2"    "DDX60"    "EIF3A"    "EIF4G1"   "EIF4G3"   "LRRFIP1" 
## [19] "MSI2"     "PRRC2C"   "SECISBP2"
## $reactome
##                                                                               category
## 26   activation of the mrna upon binding of the cap binding complex and eifs and subse
## 296                                                  eukaryotic translation initiation
## 1116                                                                       translation
##      over_represented_pvalue under_represented_pvalue numDEInCat numInCat
## 26              6.132043e-08                1.0000000          8       45
## 296             2.043390e-05                0.9999983          8       94
## 1116            5.254185e-05                0.9999951          8      106
##               FDR
## 26   7.131566e-05
## 296  1.188231e-02
## 1116 2.036872e-02
## 
## $go_bp
##                                                     category
## 608                     cytoplasmic translational initiation
## 4559                                translational initiation
## 3983                  regulation of translational initiation
## 946  formation of cytoplasmic translation initiation complex
## 607                                  cytoplasmic translation
## 3103                        protein rna complex organization
## 4672                                       viral translation
##      over_represented_pvalue under_represented_pvalue numDEInCat numInCat
## 608             0.000000e+00                1.0000000          8       16
## 4559            0.000000e+00                1.0000000         11       35
## 3983            2.968284e-09                1.0000000          7       22
## 946             2.266802e-08                1.0000000          5        9
## 607             4.539713e-07                1.0000000          9       97
## 3103            2.471536e-05                0.9999986          6       52
## 4672            3.715317e-05                0.9999997          3        6
##               FDR
## 608  0.000000e+00
## 4559 0.000000e+00
## 3983 4.641407e-06
## 946  2.658392e-05
## 607  4.259159e-04
## 3103 1.932329e-02
## 4672 2.489793e-02
## 
## [1] "set_17"
##  [1] "ARL4A"   "IL6R"    "RGCC"    "TXK"     "UBL7"    "ZC3H12A" "ZNF10"  
##  [8] "CLUH"    "COX19"   "ELMO1"   "ETV6"    "GON4L"   "LONP2"   "NAA25"  
## [15] "NFKBIZ"  "PARP14"  "PARP9"   "PDE4B"   "PHF14"   "PIGF"    "SETD2"  
## [22] "USP34"   "WDR37"   "ZNF557" 
## $go_bp
##                                          category over_represented_pvalue
## 3864 regulation of response to type ii interferon            1.212542e-05
##      under_represented_pvalue numDEInCat numInCat        FDR
## 3864                        1          3        4 0.05688035
## 
## [1] "set_21"
##  [1] "CAMK4"    "CMTM7"    "EPHX2"    "EPS8"     "FAM102A"  "HIBADH"  
##  [7] "LDLRAP1"  "NOSIP"    "RCAN3"    "SELL"     "STMN3"    "TCEA3"   
## [13] "TCF7"     "TESPA1"   "TRAV21"   "ZNF575"   "GPANK1"   "HERC3"   
## [19] "HERC6"    "ITPR2"    "MAPK8IP3" "SCRN3"    "SOS1"     "VCAN"    
## [25] "ZNF493"  
## $immune
##                                                category over_represented_pvalue
## 4253 gse45739 unstim vs acd3 acd28 stim wt cd4 tcell up            1.477794e-05
## 1959            gse22886 naive cd4 tcell vs monocyte up            4.427647e-05
## 120          gse10325 lupus cd4 tcell vs lupus bcell up            5.367498e-05
##      under_represented_pvalue numDEInCat numInCat        FDR
## 4253                0.9999992          6       38 0.07533793
## 1959                0.9999961          7       67 0.09121169
## 120                 0.9999952          7       69 0.09121169
## 
## [1] "set_23"
##  [1] "ALOX5AP" "APMAP"   "HDHD3"   "LAPTM5"  "LBH"     "LIME1"   "MATK"   
##  [8] "PTPRCAP" "PTRHD1"  "RHOC"    "THEM4"   "TMEM134" "CBX7"    "CST7"   
## [15] "FGFBP2"  "GZMA"    "GZMB"    "NKG7"    "PHC3"    "PLEK"    "SPON2"  
## [22] "SRGN"    "UBE4A"   "UCP2"   
## $immune
##                                                                               category
## 4250                           gse45739 unstim vs acd3 acd28 stim nras ko cd4 tcell dn
## 2392                                             gse26495 naive vs pd1low cd8 tcell dn
## 1967                                       gse22886 naive cd8 tcell vs memory tcell up
## 2281                                           gse25123 ctrl vs il4 stim macrophage up
## 4252                                gse45739 unstim vs acd3 acd28 stim wt cd4 tcell dn
## 1911                                              gse22886 cd8 tcell vs bcell naive up
## 1620                               gse21063 wt vs nfatc1 ko 16h anti igm stim bcell dn
## 2801                                           gse29618 pdc vs mdc day7 flu vaccine up
## 4952 hoft pbmc tice bcg rbcg ag85a ag85b age 18 40yo correlated with whole blood bacte
##      over_represented_pvalue under_represented_pvalue numDEInCat numInCat
## 4250            1.270944e-06                0.9999999          8       54
## 2392            1.042593e-05                0.9999991          8       77
## 1967            1.494111e-05                0.9999992          6       38
## 2281            2.091328e-05                0.9999988          6       41
## 4252            6.892515e-05                0.9999935          7       70
## 1911            7.560678e-05                0.9999928          7       68
## 1620            1.264718e-04                0.9999953          4       17
## 2801            1.309919e-04                0.9999919          5       35
## 4952            1.719437e-04                0.9999930          4       19
##              FDR
## 4250 0.006479275
## 2392 0.025389924
## 1967 0.025389924
## 2281 0.026653979
## 4252 0.064240557
## 1911 0.064240557
## 1620 0.083474564
## 2801 0.083474564
## 4952 0.097396579
## 
## [1] "set_27"
##  [1] "HMGCS1"   "RELT"     "TPRKB"    "CAPN15"   "DNAJC13"  "EPSTI1"  
##  [7] "GPATCH2L" "HSH2D"    "IFI44"    "IFI44L"   "IGHA1"    "IGKC"    
## [13] "MBD5"     "MX1"      "PHF11"    "PPM1K"    "PRKX"     "PTPRJ"   
## [19] "RNF213"   "S100A8"   "SPOCK2"   "STK10"    "TTC14"   
## $immune
##                                                                      category
## 3047                                   gse33424 cd161 int vs neg cd8 tcell up
## 1336                                gse18791 ctrl vs newcastle virus dc 4h dn
## 12   erwin cohen blood vaccine tc 83 age 23 48yo vaccinated vs control 7dy up
## 1290             gse17974 il4 and anti il12 vs untreated 48h act cd4 tcell dn
## 1701                                 gse21546 wt vs sap1a ko dp thymocytes up
## 2409                          gse26890 cxcr1 neg vs pos effector cd8 tcell up
## 1340                                gse18791 ctrl vs newcastle virus dc 8h dn
## 1344                             gse18791 unstim vs newcatsle virus dc 18h dn
## 2345                           gse26030 th1 vs th17 day5 post polarization up
## 375                               gse13485 ctrl vs day3 yf17d vaccine pbmc dn
##      over_represented_pvalue under_represented_pvalue numDEInCat numInCat
## 3047            4.907423e-07                1.0000000          8       57
## 1336            4.426198e-06                0.9999997          7       53
## 12              5.785920e-06                0.9999997          6       36
## 1290            7.987357e-06                0.9999996          6       36
## 1701            8.168824e-06                0.9999995          7       59
## 2409            8.668795e-06                0.9999994          7       59
## 1340            1.043667e-05                0.9999993          7       60
## 1344            2.281256e-05                0.9999986          6       45
## 2345            2.470588e-05                0.9999985          6       47
## 375             2.534133e-05                0.9999985          6       46
##              FDR
## 3047 0.002501804
## 1336 0.007365586
## 12   0.007365586
## 1290 0.007365586
## 1701 0.007365586
## 2409 0.007365586
## 1340 0.007600881
## 1344 0.012919012
## 2345 0.012919012
## 375  0.012919012
## 
## [1] "set_29"
##  [1] "CST3"     "CYB5D2"   "GALNT11"  "INTS8"    "PDE3B"    "SAE1"    
##  [7] "ADAM10"   "AHCTF1"   "ASCL2"    "CHST12"   "CTSC"     "DOPEY2"  
## [13] "FAR1"     "GALNT2"   "HLA-DQA1" "HLA-DRB1" "KLRD1"    "LILRB1"  
## [19] "LPCAT1"   "MPPE1"    "MYO9B"    "PDE12"    "PNPLA6"   "PRF1"    
## $go_bp
##                          category over_represented_pvalue
## 4472 t cell mediated cytotoxicity            1.367049e-06
##      under_represented_pvalue numDEInCat numInCat         FDR
## 4472                        1          5       14 0.006412827
## 
## [1] "set_36"
##  [1] "C10orf91"    "AC020659.1"  "ANKRD36B"    "ANKRD36C"    "BICRAL"     
##  [6] "CHD9"        "COL6A2"      "COL6A3"      "CPPED1"      "DENND4B"    
## [11] "EHBP1L1"     "IQCG"        "LAIR2"       "MINDY2"      "NLRC3"      
## [16] "RAB27B"      "RNF19A"      "SLC16A1-AS1" "SYTL3"       "TRDC"       
## [21] "TTC16"       "VPS13C"      "VTI1A"       "XCL1"        "ZNF708"     
## $reactome
##                                                         category
## 159                  collagen biosynthesis and modifying enzymes
## 160                                 collagen chain trimerization
## 72  assembly of collagen fibrils and other multimeric structures
## 162                                           collagen formation
## 590                                           ncam1 interactions
##     over_represented_pvalue under_represented_pvalue numDEInCat numInCat
## 159            9.878759e-05                1.0000000          2        2
## 160            9.878759e-05                1.0000000          2        2
## 72             2.897978e-04                0.9999992          2        3
## 162            2.897978e-04                0.9999992          2        3
## 590            2.946780e-04                0.9999992          2        3
##            FDR
## 159 0.05744498
## 160 0.05744498
## 72  0.06854210
## 162 0.06854210
## 590 0.06854210
## 
## [1] "set_37"
##  [1] "BACH2"    "EGR1"     "FOSB"     "HIST1H4C" "JUNB"     "MAF1"    
##  [7] "NUCB2"    "RGS10"    "RPL22L1"  "SEPT6"    "SNHG8"    "TSR3"    
## [13] "ACAP3"    "ARRDC3"   "CYTH1"    "FOSL2"    "JUND"     "L3HYPDH" 
## [19] "MAF"      "MIDN"     "POLR3D"  
## $reactome
##                                                      category
## 617                              ngf stimulated transcription
## 640 nuclear events kinase and transcription factor activation
## 971                                        signaling by ntrks
##     over_represented_pvalue under_represented_pvalue numDEInCat numInCat
## 617            3.003971e-06                1.0000000          4       11
## 640            8.960668e-06                0.9999999          4       14
## 971            4.757959e-05                0.9999988          4       21
##             FDR
## 617 0.003493619
## 640 0.005210628
## 971 0.018445022
## 
## [1] "set_38"
##  [1] "CD83"     "COG5"     "HMBOX1"   "IKZF2"    "KIF9"     "NXT2"    
##  [7] "ANKRD36"  "ANKRD49"  "BCL9L"    "CD226"    "COG7"     "FNBP1"   
## [13] "INPP4A"   "IRAK4"    "PPP1R16B" "RAP1GAP2" "SPN"      "SSBP3"   
## [19] "THADA"    "UVRAG"    "VPS18"    "VPS39"    "XPO6"    
## $reactome
##                           category over_represented_pvalue
## 895 sars cov 2 modulates autophagy            1.914726e-06
##     under_represented_pvalue numDEInCat numInCat         FDR
## 895                        1          3        3 0.002226826
## 
## $go_bp
##                    category over_represented_pvalue under_represented_pvalue
## 4354 snare complex assembly            2.345865e-06                        1
##      numDEInCat numInCat        FDR
## 4354          3        3 0.01100445
## 
## [1] "set_39"
##  [1] "AL136454.1" "SERINC5"    "ABCA5"      "ADHFE1"     "CHD6"      
##  [6] "DDIT4"      "DDX3Y"      "DUS1L"      "EIF1AY"     "ENOSF1"    
## [11] "FGL2"       "GBP5"       "HECTD4"     "ISG20"      "KDM5D"     
## [16] "KIAA1109"   "LPIN1"      "OSM"        "PARP11"     "RPS4Y1"    
## [21] "SBNO2"      "SUSD6"      "TARSL2"     "ZMIZ2"      "ZNF236"    
## $immune
##                                                                         category
## 5089 van den biggelaar pbmc prevnar 9mo infant stimulated vs unstimulated 8mo up
##      over_represented_pvalue under_represented_pvalue numDEInCat numInCat
## 5089            1.504061e-05                0.9999999          3        4
##             FDR
## 5089 0.07667701
saveRDS(goseq_res, sprintf("output/gene_set_enrichments_%s.RDS", 
                           file_tag))

Session information

gc()
##            used  (Mb) gc trigger  (Mb) limit (Mb) max used  (Mb)
## Ncells  8958358 478.5   16391124 875.4         NA 16391124 875.4
## Vcells 19169814 146.3   59968765 457.6      65536 91658037 699.3
sessionInfo()
## R version 4.2.3 (2023-03-15)
## Platform: aarch64-apple-darwin20 (64-bit)
## Running under: macOS Ventura 13.4.1
## 
## Matrix products: default
## BLAS:   /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/lib/libRlapack.dylib
## 
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
## 
## attached base packages:
## [1] stats4    stats     graphics  grDevices utils     datasets  methods  
## [8] base     
## 
## other attached packages:
##  [1] TxDb.Hsapiens.UCSC.hg38.knownGene_3.16.0
##  [2] GenomicFeatures_1.50.4                  
##  [3] GenomicRanges_1.50.2                    
##  [4] GenomeInfoDb_1.34.9                     
##  [5] org.Hs.eg.db_3.16.0                     
##  [6] AnnotationDbi_1.60.2                    
##  [7] IRanges_2.32.0                          
##  [8] S4Vectors_0.36.2                        
##  [9] Biobase_2.58.0                          
## [10] BiocGenerics_0.44.0                     
## [11] goseq_1.50.0                            
## [12] geneLenDataBase_1.34.0                  
## [13] BiasedUrn_2.0.10                        
## [14] fgsea_1.24.0                            
## [15] biomaRt_2.54.1                          
## [16] limma_3.54.2                            
## [17] tidyr_1.3.0                             
## [18] ggpubr_0.6.0                            
## [19] ggplot2_3.4.2                           
## [20] data.table_1.14.8                       
## 
## loaded via a namespace (and not attached):
##  [1] nlme_3.1-162                matrixStats_1.0.0          
##  [3] bitops_1.0-7                bit64_4.0.5                
##  [5] filelock_1.0.2              progress_1.2.2             
##  [7] httr_1.4.6                  tools_4.2.3                
##  [9] backports_1.4.1             bslib_0.4.2                
## [11] utf8_1.2.3                  R6_2.5.1                   
## [13] mgcv_1.8-42                 DBI_1.1.3                  
## [15] colorspace_2.1-0            withr_2.5.0                
## [17] tidyselect_1.2.0            prettyunits_1.1.1          
## [19] bit_4.0.5                   curl_5.0.1                 
## [21] compiler_4.2.3              cli_3.6.1                  
## [23] xml2_1.3.4                  DelayedArray_0.24.0        
## [25] rtracklayer_1.58.0          sass_0.4.5                 
## [27] scales_1.2.1                rappdirs_0.3.3             
## [29] Rsamtools_2.14.0            stringr_1.5.0              
## [31] digest_0.6.31               rmarkdown_2.21             
## [33] XVector_0.38.0              pkgconfig_2.0.3            
## [35] htmltools_0.5.5             MatrixGenerics_1.10.0      
## [37] dbplyr_2.3.2                fastmap_1.1.1              
## [39] rlang_1.1.0                 rstudioapi_0.14            
## [41] RSQLite_2.3.1               BiocIO_1.8.0               
## [43] jquerylib_0.1.4             generics_0.1.3             
## [45] jsonlite_1.8.4              BiocParallel_1.32.6        
## [47] dplyr_1.1.2                 car_3.1-2                  
## [49] RCurl_1.98-1.12             magrittr_2.0.3             
## [51] GO.db_3.16.0                GenomeInfoDbData_1.2.9     
## [53] Matrix_1.6-4                Rcpp_1.0.10                
## [55] munsell_0.5.0               fansi_1.0.4                
## [57] abind_1.4-5                 lifecycle_1.0.3            
## [59] stringi_1.7.12              yaml_2.3.7                 
## [61] carData_3.0-5               SummarizedExperiment_1.28.0
## [63] zlibbioc_1.44.0             BiocFileCache_2.6.1        
## [65] grid_4.2.3                  blob_1.2.4                 
## [67] parallel_4.2.3              crayon_1.5.2               
## [69] lattice_0.20-45             splines_4.2.3              
## [71] Biostrings_2.66.0           cowplot_1.1.1              
## [73] hms_1.1.3                   KEGGREST_1.38.0            
## [75] knitr_1.44                  pillar_1.9.0               
## [77] rjson_0.2.21                ggsignif_0.6.4             
## [79] codetools_0.2-19            fastmatch_1.1-3            
## [81] XML_3.99-0.14               glue_1.6.2                 
## [83] evaluate_0.20               png_0.1-8                  
## [85] vctrs_0.6.2                 gtable_0.3.3               
## [87] purrr_1.0.1                 cachem_1.0.7               
## [89] xfun_0.39                   broom_1.0.4                
## [91] restfulr_0.0.15             rstatix_0.7.2              
## [93] tibble_3.2.1                GenomicAlignments_1.34.1   
## [95] memoise_2.0.1